US20190361116A1 - Apparatus and method for high-speed tracking of vessel - Google Patents

Apparatus and method for high-speed tracking of vessel Download PDF

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Publication number
US20190361116A1
US20190361116A1 US16/412,507 US201916412507A US2019361116A1 US 20190361116 A1 US20190361116 A1 US 20190361116A1 US 201916412507 A US201916412507 A US 201916412507A US 2019361116 A1 US2019361116 A1 US 2019361116A1
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Prior art keywords
tracking
vessel
objects
advance
targets
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Byung-Gil LEE
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Electronics and Telecommunications Research Institute ETRI
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Electronics and Telecommunications Research Institute ETRI
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    • G01S13/9307—
    • G—PHYSICS
    • G01—MEASURING; TESTING
    • G01S—RADIO DIRECTION-FINDING; RADIO NAVIGATION; DETERMINING DISTANCE OR VELOCITY BY USE OF RADIO WAVES; LOCATING OR PRESENCE-DETECTING BY USE OF THE REFLECTION OR RERADIATION OF RADIO WAVES; ANALOGOUS ARRANGEMENTS USING OTHER WAVES
    • G01S13/00—Systems using the reflection or reradiation of radio waves, e.g. radar systems; Analogous systems using reflection or reradiation of waves whose nature or wavelength is irrelevant or unspecified
    • G01S13/88—Radar or analogous systems specially adapted for specific applications
    • G01S13/93—Radar or analogous systems specially adapted for specific applications for anti-collision purposes
    • G01S13/937—Radar or analogous systems specially adapted for specific applications for anti-collision purposes of marine craft
    • G—PHYSICS
    • G08—SIGNALLING
    • G08G—TRAFFIC CONTROL SYSTEMS
    • G08G3/00—Traffic control systems for marine craft
    • G08G3/02—Anti-collision systems
    • G—PHYSICS
    • G01—MEASURING; TESTING
    • G01S—RADIO DIRECTION-FINDING; RADIO NAVIGATION; DETERMINING DISTANCE OR VELOCITY BY USE OF RADIO WAVES; LOCATING OR PRESENCE-DETECTING BY USE OF THE REFLECTION OR RERADIATION OF RADIO WAVES; ANALOGOUS ARRANGEMENTS USING OTHER WAVES
    • G01S13/00—Systems using the reflection or reradiation of radio waves, e.g. radar systems; Analogous systems using reflection or reradiation of waves whose nature or wavelength is irrelevant or unspecified
    • G01S13/66—Radar-tracking systems; Analogous systems
    • G—PHYSICS
    • G01—MEASURING; TESTING
    • G01S—RADIO DIRECTION-FINDING; RADIO NAVIGATION; DETERMINING DISTANCE OR VELOCITY BY USE OF RADIO WAVES; LOCATING OR PRESENCE-DETECTING BY USE OF THE REFLECTION OR RERADIATION OF RADIO WAVES; ANALOGOUS ARRANGEMENTS USING OTHER WAVES
    • G01S13/00—Systems using the reflection or reradiation of radio waves, e.g. radar systems; Analogous systems using reflection or reradiation of waves whose nature or wavelength is irrelevant or unspecified
    • G01S13/66—Radar-tracking systems; Analogous systems
    • G01S13/72—Radar-tracking systems; Analogous systems for two-dimensional tracking, e.g. combination of angle and range tracking, track-while-scan radar
    • G01S13/723—Radar-tracking systems; Analogous systems for two-dimensional tracking, e.g. combination of angle and range tracking, track-while-scan radar by using numerical data
    • G01S13/726—Multiple target tracking
    • G—PHYSICS
    • G01—MEASURING; TESTING
    • G01S—RADIO DIRECTION-FINDING; RADIO NAVIGATION; DETERMINING DISTANCE OR VELOCITY BY USE OF RADIO WAVES; LOCATING OR PRESENCE-DETECTING BY USE OF THE REFLECTION OR RERADIATION OF RADIO WAVES; ANALOGOUS ARRANGEMENTS USING OTHER WAVES
    • G01S13/00—Systems using the reflection or reradiation of radio waves, e.g. radar systems; Analogous systems using reflection or reradiation of waves whose nature or wavelength is irrelevant or unspecified
    • G01S13/88—Radar or analogous systems specially adapted for specific applications
    • G01S13/91—Radar or analogous systems specially adapted for specific applications for traffic control
    • G01S13/917—Radar or analogous systems specially adapted for specific applications for traffic control for marine craft or other waterborne vessels
    • G—PHYSICS
    • G01—MEASURING; TESTING
    • G01S—RADIO DIRECTION-FINDING; RADIO NAVIGATION; DETERMINING DISTANCE OR VELOCITY BY USE OF RADIO WAVES; LOCATING OR PRESENCE-DETECTING BY USE OF THE REFLECTION OR RERADIATION OF RADIO WAVES; ANALOGOUS ARRANGEMENTS USING OTHER WAVES
    • G01S7/00—Details of systems according to groups G01S13/00, G01S15/00, G01S17/00
    • G01S7/02—Details of systems according to groups G01S13/00, G01S15/00, G01S17/00 of systems according to group G01S13/00
    • G01S7/28—Details of pulse systems
    • G01S7/285—Receivers
    • G01S7/292—Extracting wanted echo-signals
    • G01S7/2923—Extracting wanted echo-signals based on data belonging to a number of consecutive radar periods
    • G01S7/2927—Extracting wanted echo-signals based on data belonging to a number of consecutive radar periods by deriving and controlling a threshold value
    • G—PHYSICS
    • G06—COMPUTING; CALCULATING OR COUNTING
    • G06N—COMPUTING ARRANGEMENTS BASED ON SPECIFIC COMPUTATIONAL MODELS
    • G06N20/00—Machine learning
    • G—PHYSICS
    • G01—MEASURING; TESTING
    • G01S—RADIO DIRECTION-FINDING; RADIO NAVIGATION; DETERMINING DISTANCE OR VELOCITY BY USE OF RADIO WAVES; LOCATING OR PRESENCE-DETECTING BY USE OF THE REFLECTION OR RERADIATION OF RADIO WAVES; ANALOGOUS ARRANGEMENTS USING OTHER WAVES
    • G01S13/00—Systems using the reflection or reradiation of radio waves, e.g. radar systems; Analogous systems using reflection or reradiation of waves whose nature or wavelength is irrelevant or unspecified
    • G01S13/86—Combinations of radar systems with non-radar systems, e.g. sonar, direction finder

Definitions

  • the present invention relates generally to technology for high-speed tracking of a vessel, and more particularly to technology for enabling high-speed tracking in response to a request to track a vessel by selecting a target and performing advance tracking for the selected target.
  • VTS Vessel Traffic Service
  • a Vessel Traffic Service (VTS) personnel performs traffic control by keeping his or her eyes on a screen on which the positions of vessels are displayed, by predicting whether a collision between vessels will occur by checking the distance therebetween based on his or her work experience, and by modifying the sailing paths of vessels that are determined to be highly likely to collide with each other.
  • each vessel identifies neighboring vessels using a radar device or the like installed therein and sails with reference to the identified information.
  • each vessel may transmit vessel information, including the identification information thereof, to a control center using an Automatic Identification System (AIS), whereby the control center may clearly detect the vessel located at a specific position on the sea.
  • AIS Automatic Identification System
  • the AIS installed in a vessel transmits Maritime Mobile Service Identity (MMSI) information, through which the vessel can be automatically identified, position information, dynamic information, and the like to the control center, thereby facilitating identification of the vessel and detection of the position thereof and improving control efficiency.
  • MMSI Maritime Mobile Service Identity
  • the vessel traffic control system may detect the positions and speeds of vessels by receiving not only AIS information but also data sensed using radar, which is a different kind of sensor. Tracking a target using radar may be performed by analyzing information about many unspecified objects, which is received by a radar transceiver, by extracting the motion characteristics of the corresponding target, and by continuously predicting the movement of the corresponding target.
  • a mathematical filter such as a Kalman filter, or the like, is used as a tracking filter in order to minimize the number of tracking errors.
  • the tracking filter performs real-time tracking using a dynamic filtering method, in which prediction and updates are repeated.
  • a dynamic filtering method in which prediction and updates are repeated.
  • the target object when the target object is selected using a single radar image, many errors may occur, and it is difficult to correctly perform control.
  • the target object When a VTS personnel urgently requires information pertaining to the risk of collision, the target object may be tracked through a single radar scan, but many errors may occur in this case.
  • a prediction error in the process of predicting the movement of a vessel causes damping, whereby a direction line indicative of the direction of the movement of the vessel is made unclear.
  • Patent Document 1 Korean Patent No. 10-1758576, published on Jul. 17, 2017 and titled “Method and apparatus for detecting object with radar and camera”.
  • An object of the present invention is to select an object that looks like a vessel as the advance tracking target, to perform advance tracking, and to quickly track a vessel using the result of advance tracking.
  • Another object of the present invention is to quickly recognize the risk of a collision between vessels and to quickly respond thereto.
  • a further object of the present invention is to preferentially process the advance tracking target, which is an object that looks like a vessel, thereby reducing the number of erroneously detected elements.
  • Yet another object of the present invention is to set a threshold for the number of objects to be extracted and the maximum number of advance tracking targets, thereby preventing an apparatus for high-speed tracking of a vessel from being overloaded.
  • a method for high-speed tracking of a vessel performed by an apparatus for high-speed tracking of the vessel, includes processing a reflected radar signal that is input; extracting objects from the reflected radar signal that is processed; selecting targets from among the extracted objects; performing advance tracking of the selected targets; and tracking the vessel using the result of advance tracking when an instruction to track the vessel is received.
  • selecting the targets may be configured to select a number of objects corresponding to the maximum number of advance tracking targets as the targets based on a priority assigned to each of the extracted objects.
  • the priority may be set based on at least one of the cell size and the cell signal strength of the reflected radar signal corresponding to the object.
  • the priority may be set based on a result of machine learning performed on information about the extracted objects.
  • selecting the targets may be configured to perform machine learning using a model that is trained on image data corresponding to an actual vessel in radar image information and to select the targets based on the result of machine learning.
  • selecting the targets may include setting a selection weight for each of the objects based on at least one of the cell size and the cell signal strength of the reflected radar signal corresponding to the object; performing a primary sort on the objects based on the selection weight; performing a secondary sort on the objects by performing machine learning for the objects listed according to the primary sort; and selecting a number of objects corresponding to the maximum number of advance tracking targets as the targets, among the objects listed according to the secondary sort.
  • performing advance tracking may include setting a gate based on the priority of each of the targets; generating multiple pieces of preliminary track data by predicting the track of the target; generating an advance tracking result for the target by combining the multiple pieces of preliminary track data; and storing the generated advance tracking result.
  • generating the advance tracking result may be configured to generate the advance tracking result by setting a tracking weight for the target based on a result of machine learning performed using radar image information and by combining the multiple pieces of preliminary track data for the target for which the tracking weight is set.
  • extracting the objects may be configured to extract the object when the amplitude of the reflected radar signal is equal to or greater than a threshold amplitude.
  • an apparatus for high-speed tracking of a vessel includes a preprocessing unit for processing a reflected radar signal that is input thereto; an object extraction unit for extracting objects from the reflected radar signal that is processed; an advance tracking target selection unit for selecting targets from among the extracted objects; an advance tracking unit for performing advance tracking of the selected targets; and a high-speed vessel-tracking unit for tracking the vessel using the result of advance tracking when an instruction to track the vessel is received.
  • the advance tracking target selection unit may select a number of objects corresponding to the maximum number of advance tracking targets as the targets based on a priority assigned to each of the extracted objects.
  • the priority may be set based on at least one of the cell size and the cell signal strength of the reflected radar signal corresponding to the object.
  • the priority may be set based on a result of machine learning performed on information about the extracted objects.
  • the advance tracking target selection unit may perform machine learning using a model trained on image data corresponding to an actual vessel in radar image information and select the targets based on the result of machine learning.
  • the advance tracking target selection unit may set a selection weight for each of the objects based on at least one of the cell size and the cell signal strength of the reflected radar signal corresponding to the object, perform a primary sort on the objects based on the selection weight, perform a secondary sort on the objects by performing machine learning for the objects listed according to the primary sort, and select a number of objects corresponding to the maximum number of advance tracking targets as the targets, among the objects listed according to the secondary sort.
  • the advance tracking unit may set a gate based on the priority of each of the targets, generate multiple pieces of preliminary track data by predicting the track of the target, generate an advance tracking result for the target by combining the multiple pieces of preliminary track data, and store the generated advance tracking result.
  • the advance tracking unit may generate the advance tracking result by setting a tracking weight for the target based on a result of machine learning performed using radar image information and by combining the multiple pieces of preliminary track data for the target for which the tracking weight is set.
  • the object extraction unit may extract the object when the amplitude of the reflected radar signal is equal to or greater than a threshold amplitude.
  • FIG. 1 is a view that schematically shows an environment in which an apparatus for high-speed tracking of a vessel according to an embodiment of the present invention is applied;
  • FIG. 2 is a block diagram that shows the configuration of an apparatus for high-speed tracking of a vessel according to an embodiment of the present invention
  • FIG. 3 is a flowchart for explaining a method for high-speed tracking of a vessel according to an embodiment of the present invention
  • FIG. 4 is a view for explaining a high-speed vessel-tracking process of a vessel traffic control system according to an embodiment of the present invention
  • FIG. 5 is a flowchart for explaining the process of selecting the advance tracking target according to an embodiment of the present invention.
  • FIG. 6 is a flowchart for explaining an advance tracking process according to an embodiment of the present invention.
  • FIG. 7 is a block diagram that shows a computer system according to an embodiment of the present invention.
  • FIG. 1 is a view that schematically shows an environment in which an apparatus for high-speed tracking of a vessel according to an embodiment of the present invention is applied.
  • the high-speed vessel-tracking apparatus 200 receives data from at least one radar device 100 and at least one AIS base station 150 , thereby quickly tracking a vessel. Also, the high-speed vessel-tracking apparatus 200 may transmit the result of vessel tracking to a vessel traffic control center 310 or output the same through a vessel display device 320 .
  • the radar device 100 may be 2D sea surveillance radar, and the antenna thereof may transmit a signal by rotating at regular intervals and receive a signal reflected from elements of the marine environment.
  • the received signal may include signals and noise reflected from objects, such as a vessel and the like, clutter from terrain such as islands or shores, clutter from waves or the like, and clutter from snow, rain, or the like.
  • the radar device 100 collects radar images presented in the form of a distance and azimuth in a polar coordinate system.
  • the collected radar images may be B-Scope data, and may be a Plan Position Indicator (PPI) radar image transformed into an orthogonal coordinate system.
  • PPI Plan Position Indicator
  • the AIS base station 150 may receive Maritime Mobile Service Identity (MMSI) information for automatic identification of a vessel, position information, dynamic information, and the like from an Automatic Identification System (AIS) installed in the vessel and transmit the same to the high-speed vessel-tracking apparatus 200 .
  • MMSI Maritime Mobile Service Identity
  • AIS Automatic Identification System
  • the high-speed vessel-tracking apparatus 200 receives a reflected radar signal from the radar device 100 , processes the same, and extracts objects therefrom. Then, the high-speed vessel-tracking apparatus 200 selects an advance tracking target from among the extracted objects, performs advance tracking for the selected target, and stores the result thereof.
  • the high-speed vessel-tracking apparatus 200 may perform high-speed tracking of the vessel using the result of advance tracking.
  • the high-speed vessel-tracking apparatus 200 may use the information received from the AIS base station 150 when it performs advance tracking or high-speed tracking.
  • the high-speed vessel-tracking apparatus 200 tracks a vessel corresponding to an instruction using information acquired through advance tracking, thereby reducing the time taken to track the vessel. Also, the high-speed vessel-tracking apparatus 200 tracks a vessel in an urgent situation, thereby helping the operator of the vessel and a VTS personnel make a decision.
  • the high-speed vessel-tracking apparatus 200 selects an object that looks like a vessel as the advance tracking target and preferentially processes the selected target, thereby reducing the number of erroneously detected elements and improving the accuracy of vessel tracking.
  • FIG. 2 is a block diagram that shows the configuration of an apparatus for high-speed tracking of a vessel according to an embodiment of the present invention.
  • the high-speed vessel-tracking apparatus 200 includes a preprocessing unit 210 , an object extraction unit 220 , an advance tracking target selection unit 230 , an advance tracking unit 240 , and a high-speed vessel-tracking unit 250 .
  • the preprocessing unit 210 processes a reflected radar signal that is input thereto.
  • the reflected radar signal includes signals and noise reflected from clutter sources, such as clutter from terrain such as islands or shores, clutter from waves or the like, and clutter from snow, rain, or the like. Accordingly, the preprocessing unit 210 eliminates the clutter and noise by processing the reflected radar signal before advance tracking of a vessel is performed.
  • the preprocessing unit 210 may eliminate sea clutter and the like by performing multiple stages of raw data signal processing.
  • the result of signal processing performed by the preprocessing unit 210 includes large clutter that is not eliminated by a filter and information about the actual vessel, which is weakened through signal processing.
  • the clutter and the information about the actual vessel are not easily distinguished from each other, and the signal processing result may be transmitted to the vessel traffic control center 310 or the vessel display device 320 and displayed in the form of an upper layer on an electronic navigational chart.
  • the object extraction unit 220 extracts objects from the reflected radar signal on which signal processing is performed.
  • the object extraction unit 220 may extract an object.
  • Conventional control systems are configured such that, when a VTS personnel inputs a tracking instruction for an image assumed to be a vessel, a target object is extracted and tracked, and information thereabout is delivered.
  • a vessel is determined using only a single piece of scan information in response to the request for fast tracking from a VTS personnel who monitors the risk of a collision, many errors may occur, and a prediction error, which is an error occurring when the movement of a vessel is predicted, causes damping, whereby a direction line indicative of the direction of the vessel becomes unclear.
  • a prediction error which is an error occurring when the movement of a vessel is predicted, causes damping, whereby a direction line indicative of the direction of the vessel becomes unclear.
  • a lot of time is taken to track the vessel. For example, when scanning is performed every three seconds and when a vessel is tracked using four pieces of scan information, it takes 15 or more seconds to track the vessel.
  • the high-speed vessel-tracking apparatus 200 extracts an object when the amplitude of the reflected radar signal is greater than a threshold amplitude, selects a target from among the extracted objects, performs advance tracking for the target, and uses the result of advance tracking. Accordingly, the high-speed vessel-tracking apparatus 200 may track a vessel using multiple pieces of scan information, thereby improving accuracy. Also, the time taken to track the vessel may be reduced by tracking the vessel using the result of advance tracking.
  • the advance tracking target selection unit 230 selects the advance tracking target from among the extracted objects.
  • the advance tracking target selection unit 230 may select a number of objects corresponding to the maximum number of advance tracking targets as the advance tracking targets based on the priorities assigned to the extracted objects.
  • the advance tracking target selection unit 230 may set a cell size and the sum of the strengths of cell signals corresponding to each object as weights, and may sequentially assign object IDs to the objects in descending order based on the sum of the energy strengths of each cell.
  • the advance tracking target selection unit 230 sets the sum of the strengths of cell signals, corresponding to the pixels on the radar image, and the area, corresponding to a size, as the weights, and assigns the object ID based thereon.
  • the advance tracking target selection unit 230 may select a number of objects corresponding to the maximum number of advance tracking targets as the advance tracking targets based on the object IDs thereof. For example, when the maximum number of advance tracking targets is 20, the advance tracking target selection unit 230 may select the top 20 objects as the advance tracking targets, among the objects listed in order of object ID.
  • the advance tracking target selection unit 230 may perform machine learning using a model that is trained on image data corresponding to an actual vessel in radar image information, and may select the advance tracking targets based on the result of machine learning.
  • the advance tracking target selection unit 230 may set a selection weight for an object based on at least one of the cell size and the cell signal strength of a reflected radar signal corresponding to the object. Then, the advance tracking target selection unit 230 performs a primary sort on the objects based on the selection weight, performs a secondary sort on the objects by performing machine learning for the objects listed according to the primary sort, and selects a number of objects corresponding to the maximum number of advance tracking targets as the advance tracking targets, among the objects listed according to the secondary sort.
  • the advance tracking target selection unit 230 may select a preset number of objects from the objects listed according to the primary sort, perform machine learning for the selected objects, and select a preset number of objects as the advance tracking targets using the result of machine learning.
  • the advance tracking unit 240 may perform advance tracking for each of the advance tracking targets and store the result thereof.
  • the advance tracking unit 240 may set a gate based on the priority of the target and generate preliminary track data by predicting the track of the target. Also, the advance tracking unit 240 may generate an advance tracking result for the target by combining multiple pieces of preliminary track data and store the generated advance tracking result.
  • the advance tracking unit 240 sets a tracking weight for the target based on the result of machine learning performed using radar image information and combines the preliminary tracks for the target, for which the tracking weight is set, thereby generating the advance tracking result.
  • the high-speed vessel-tracking unit 250 tracks a vessel using the result of advance tracking when an instruction to track the vessel is received.
  • the high-speed vessel-tracking unit 250 does not cause damping because it uses the result of advance tracking when it tracks a vessel. Also, because advance tracking has been performed using multiple pieces of scan information each time scanning is performed after the high-speed vessel-tracking apparatus 200 is first operated, tracking may be stably performed compared to the conventional method, in which a vessel is tracked from the outset.
  • FIG. 3 is a flowchart for explaining a method for high-speed tracking of a vessel according to an embodiment of the present invention
  • FIG. 4 is a view for explaining the high-speed vessel-tracking process of a vessel traffic control system according to an embodiment of the present invention.
  • the high-speed vessel-tracking apparatus 200 receives a reflected radar signal from the radar device 100 and processes the reflected radar signal at step S 310 .
  • the high-speed vessel-tracking apparatus 200 extracts objects from the reflected radar signal at step S 320 .
  • the high-speed vessel-tracking apparatus 200 may extract an object when the amplitude of the reflected radar signal, on which signal processing is performed, is greater than a threshold amplitude.
  • the high-speed vessel-tracking apparatus 200 sets a threshold for the number of objects to be extracted, and may extract objects such that the number thereof is less than the threshold.
  • the high-speed vessel-tracking apparatus 200 may compress information about the extracted objects and transmit the same to a fusion system such that a radar object is automatically combined with AIS information and tracked, and may perform a process to be described later using the information about the extracted objects.
  • the high-speed vessel-tracking apparatus 200 selects advance tracking targets at step S 330 .
  • the high-speed vessel-tracking apparatus 200 selects advance tracking targets.
  • the high-speed vessel-tracking apparatus 200 may set a cell size and the sum of the strengths of cell signals, corresponding to an object, as weights, and may select a number of objects corresponding to the maximum number of advance tracking targets as the advance tracking targets, among the objects extracted at step S 320 .
  • the high-speed vessel-tracking apparatus 200 may extract the targets using a model that performs deep learning, in which case a number of objects corresponding to the maximum number of advance tracking targets may be selected as the targets.
  • the maximum number of advance tracking targets may vary depending on the result of signal processing performed at step S 320 . Because the number of extracted objects may significantly increase or decrease depending on the value of a parameter (a CFAR parameter) in the process of extracting objects, unless the high-speed vessel-tracking apparatus 200 sets a maximum permissible number, the system thereof may be shut down due to a high computational load in the tracking process.
  • a parameter a CFAR parameter
  • the high-speed vessel-tracking apparatus 200 sets the maximum permissible number and sets a value less than the maximum permissible number as the maximum number of advance tracking targets, thereby limiting the number of advance tracking targets.
  • the high-speed vessel-tracking apparatus 200 may set the threshold for the number of objects to be extracted and the maximum number of advance tracking targets depending on the set parameter.
  • the high-speed vessel-tracking apparatus 200 selects objects that are assumed to be vessels as the advance tracking targets, performs advance tracking for the selected targets, and tracks a vessel based on the result of advance tracking, thereby reducing the time taken to track the vessel and improving the accuracy of vessel tracking.
  • the high-speed vessel-tracking apparatus 200 performs advance tracking for the target and stores the result thereof at step S 340 .
  • the high-speed vessel-tracking apparatus 200 may set a gate based on the priority of the target, generate preliminary track data by predicting the track of the target, and generate an advance tracking result for the target by combining multiple pieces of preliminary track data. In other words, the high-speed vessel-tracking apparatus 200 performs advance tracking before a VTS personnel inputs an instruction to track a vessel, thereby performing part of the vessel-tracking process in advance.
  • the high-speed vessel-tracking apparatus 200 tracks the vessel at step S 360 .
  • the high-speed vessel-tracking apparatus 200 may quickly track the vessel using the advance tracking result.
  • FIG. 5 is a flowchart for explaining the process of selecting an advance tracking target according to an embodiment of the present invention.
  • the high-speed vessel-tracking apparatus 200 sets a selection weight for each object based on a cell size and a cell signal strength corresponding to the object at step S 510 .
  • the high-speed vessel-tracking apparatus 200 sets the selection weight for each of the objects based on the cell size and the cell signal strength thereof.
  • the high-speed vessel-tracking apparatus 200 performs a primary sort on the objects based on the selection weights at step S 520 .
  • the high-speed vessel-tracking apparatus 200 selects a preset number of objects from the sorted object list, and may perform the process of step S 530 only for the selected objects.
  • the high-speed vessel-tracking apparatus 200 performs machine learning at step S 530 and performs a secondary sort on the objects based on the result of machine learning at step S 540 .
  • the high-speed vessel-tracking apparatus 200 may perform machine learning for the selected objects and perform the secondary sort based on the result of machine learning.
  • the high-speed vessel-tracking apparatus 200 selects the advance tracking targets from among the objects listed according to the secondary sort at step S 550 .
  • the high-speed vessel-tracking apparatus 200 may select a number of objects corresponding to the maximum number of advance tracking targets as the advance tracking targets. Then, the high-speed vessel-tracking apparatus 200 may perform advance tracking for the selected targets by performing step S 340 in FIG. 3 .
  • FIG. 6 is a flowchart for explaining the process of advance tracking according to an embodiment of the present invention.
  • the high-speed vessel-tracking apparatus 200 initializes preliminary tracks and sets a gate, which is a tracking range, at step S 610 .
  • the high-speed vessel-tracking apparatus 200 may perform advance tracking for each of the targets as shown in FIG. 6 .
  • the high-speed vessel-tracking apparatus 200 initializes the preliminary tracks, generates preliminary track information, and sets a gate.
  • the high-speed vessel-tracking apparatus 200 may initialize the preliminary tracks and set the gate based on the object ID assigned to the target.
  • the high-speed vessel-tracking apparatus 200 generates preliminary track data at step S 620 .
  • the high-speed vessel-tracking apparatus 200 may generate preliminary track data by predicting the track of the target.
  • the high-speed vessel-tracking apparatus 200 generates an advance tracking result and stores the generated advance tracking result at step S 630 .
  • the high-speed vessel-tracking apparatus 200 may generate the advance tracking result for the target by combining the pieces of preliminary track data and store the generated advance tracking result.
  • the high-speed vessel-tracking apparatus 200 may update the position, the speed, the state information, and the like of the track in the preliminary track list, and may predict the position of the track, which is to be acquired through the next scan.
  • the advance tracking result generated and stored at step S 630 is used when high-speed tracking is performed in response to an instruction to track a vessel, which is received at step S 350 in FIG. 3 . Also, the high-speed vessel-tracking apparatus 200 may calculate the correlation between the tracks and extract a parameter based on the correlation.
  • FIG. 7 is a block diagram that shows a computer system according to an embodiment of the present invention.
  • an embodiment of the present invention may be implemented in a computer system 700 including a computer-readable recording medium.
  • the computer system 700 may include one or more processors 710 , memory 730 , a user-interface input device 740 , a user-interface output device 750 , and storage 760 , which communicate with each other via a bus 720 .
  • the computer system 700 may further include a network interface 770 connected to a network 780 .
  • the processor 710 may be a central processing unit or a semiconductor device for executing processing instructions stored in the memory 730 or the storage 760 .
  • the memory 730 and the storage 760 may be various types of volatile or nonvolatile storage media.
  • the memory may include ROM 731 or RAM 732 .
  • an embodiment of the present invention may be implemented as a nonvolatile computer-readable storage medium in which methods implemented using a computer or instructions executable in a computer are recorded.
  • the computer-readable instructions When executed by a processor, the computer-readable instructions may perform a method according to at least one aspect of the present invention.
  • advance tracking is performed by selecting an object that looks like a vessel as the target thereof, and a vessel may be quickly tracked using the result of advance tracking.
  • the risk of a collision between vessels may be quickly recognized, whereby it is possible to quickly respond thereto.
  • the advance tracking target which is an object that looks like a vessel, is preferentially processed, whereby the number of erroneously detected elements may be reduced.
  • a threshold for the number of objects to be extracted and the maximum number of advance tracking targets may be set, whereby an apparatus for high-speed tracking of a vessel may be prevented from being overloaded.
  • the apparatus and method for high-speed tracking of a vessel according to the present invention are not limitedly applied to the configurations and operations of the above-described embodiments, but all or some of the embodiments may be selectively combined and configured, so that the embodiments may be modified in various ways.

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US11501119B2 (en) 2020-02-24 2022-11-15 Electronics And Telecommunications Research Institute Apparatus and method for identifying warship
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